Varaico: Literature-Extracted Genetic Variants

Gene:TP53
Variant:p.Q100K
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TP53

NM_000546.6:p.Q100K

Associated Papers

Neoantigenic properties of TP53 variants influence cancer risk in individuals with Li-Fraumeni syndrome.

Montellier E et al.

Ebiomedicine, 2026

41370968 (PubMed )
Supplement: mmc2.xlsx › Table_S1

A prospective, multicenter, comprehensive genomic profile signature study in patients with EGFR-mutant advanced non-small cell lung cancer at the first-line treatment failure of osimertinib.

Shi Y et al.

Signal Transduction and Targeted Therapy, 2025

41326340 (PubMed )
Supplement: 41392_2025_2481_MOESM1_ESM.docx

A quantitative, Bayesian-informed approach to gene-specific variant classification: Updated Expert Panel recommendations improve classification of TP53 germline variants for Li-Fraumeni syndrome.

Fortuno C et al.

Genome Medicine, 2025

41126324 (PubMed )
Supplement: 13073_2025_1536_MOESM2_ESM.xlsx › Table_S2

Detection of clinically relevant variants in the TP53 gene below 10% allelic frequency: A multicenter study by ERIC, the European Research Initiative on CLL.

Pavlova S et al.

Hemasphere, 2025

39840379 (PubMed )
Supplement: HEM3-9-e70065-s001.xlsx › Table_S5

Clustering of TP53 variants into functional classes correlates with cancer risk and identifies different phenotypes of Li-Fraumeni syndrome.

Montellier E et al.

Iscience, 2024

39634561 (PubMed )
Supplement: mmc2.xlsx › TableS1

Different impacts of TP53 mutations on cell cycle-related gene expression among cancer types.

Sasaki K et al.

Scientific Reports, 2023

36964217 (PubMed )
Supplement: 41598_2023_32092_MOESM1_ESM.xlsx › Suppl._table_S1

TP53_PROF: a machine learning model to predict impact of missense mutations in TP53.

Ben-Cohen G et al.

Briefings in Bioinformatics, 2022

35043155 (PubMed )
Supplement: supplementary_table_s1_bbab524.xlsx › S1B._Negative_Set

Pan-urologic cancer genomic subtypes that transcend tissue of origin.

Chen F et al.

Nature Communications, 2017

28775315 (PubMed )
Supplement: 41467_2017_289_MOESM7_ESM.xlsx › mutation_data

Bioinformatics study of cancer-related mutations within p53 phosphorylation site motifs.

Ji X et al.

International Journal of Molecular Sciences, 2014

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